Table containing island-level summary of a) changes in land area and b) position change in the shoreline.

uCT and histology datasets General information The rat was in the oestrus phase of its cycle. All slices are along the transverse plane. The organ was stained with PhosphoTungstic Acid (PTA) and the histology slices used Hematoxylin and Eosin (HE) stain. Contents The AWA015_PTA_1_Rec_Trans.zip archive contains the original uCT dataset of the full rat...

This paper presents a comprehensive and quality collection of functional human brain network data for potential research in the intersection of neuroscience, machine learning, and graph analytics. Anatomical and functional MRI images of the brain have been used to understand the functional connectivity of the human brain and are particularly important in...

Supplementary Tables for Chapter 2

Supplementary Tables for Chapter 3

Supplementary Tables for Chapter 4

Gene Regulatory Network for melanocyte (mc), sun-exposed skin (SE), not sun-exposed skin (NSE), and blood

Supplementary File 1 Supplementary File 2

This is the data set that is used for this paper.

New Zealand's Coastal Change Dataset is comprised of two datasets; coastlines (NZCCD Coastlines) and rates (NZCCD Coastal Change Rates) datasets. NZCCD Coastlines: The coastlines dataset comprises all New Zealand’s mapped coastal positions from the 1940’s to 2023, mapped from both historic aerial imagery and high-resolution satellite imagery. NZCCD Rates:...

Identifying suitable donors for faecal microbiota transplantation (FMT) is complex, costly, and time-consuming. Here, we present the donor data set for the gut bugs trial. This is published as part of Donor screening outcomes for faecal microbiota transplantation: from recruitment to encapsulation. Brooke C. Wilsona,b,#, Ry Y. Tweedie-Cullena,#, Taygen...

Identifying suitable donors for faecal microbiota transplantation (FMT) is complex, costly, and time-consuming. Here, we present the donor data set for the gut bugs trial. This is published as part of Donor screening outcomes for faecal microbiota transplantation: from recruitment to encapsulation. Brooke C. Wilsona,b,#, Ry Y. Tweedie-Cullena,#, Taygen...

A tissue-specific gene regulatory network (GRN) was generated for brain cortex tissue using 1) Hi-C dataset from dorsolateral prefrontal cortex cells 2) GTEx eQTL dataset from brain cortex tissue.

A tissue-specific gene regulatory network (GRN) was generated for the whole blood using 1) Hi-C dataset from peripheral blood B cells, T cells, CD4+ T cells, and CD8+ T cells 2) GTEx eQTL dataset from whole-blood

A tissue-specific gene regulatory network (GRN) was generated for the artery aorta using, 1) Hi-C dataset from coronary artery smooth muscle cells, left ventricle cells, aorta cells, and TeloHAEC cells 2) GTEx eQTL dataset from artery aorta tissue.

A tissue-specific gene regulatory network (GRN) was generated for coronary artery tissue using, 1) Hi-C dataset from coronary artery smooth muscle cells, left ventricle cells, aorta cells, and TeloHAEC cells 2) GTEx eQTL dataset from coronary artery

A tissue-specific gene regulatory network (GRN) was generated for the lung tissue using, 1) Hi-C dataset from lung cells 2) GTEx eQTL dataset from lung tissue.

A tissue-specific gene regulatory network (GRN) was generated for liver tissue using, 1) Hi-C dataset from HepG2 cells, liver cells, and endothelial hepatic sinusoid cells 2) GTEx eQTL dataset from liver tissue

A tissue-specific gene regulatory network (GRN) was generated for skin sun-exposed lower leg tissue using, 1) Hi-C dataset from NHEK, RPMI7951, and SK-MEL-5 cells 2) GTEx eQTL dataset from skin sun-exposed lower leg tissue

A tissue-specific gene regulatory network (GRN) was generated for skin not sun-exposed suprapubic tissue using, 1) Hi-C dataset from NHEK, RPMI7951, and SK-MEL-5 cells 2) GTEx eQTL dataset from skin not sun-exposed suprapubic tissue